Pinned Repositories
10k_genomes
Various scripts for efficient processing of 10k Salmonella genomes
2015lab1
2019-snakemake-Harvard-Informatics-nanocourse
Intro to workflows for efficient automated data analysis, using snakemake.
2020-CS109A
2020-Genome_Assembly_Workshop
Explore the world of genome assembly and gain an understanding of the power and pitfalls of sequencing technologies and assembly techniques.
2020_group07
An exploratory proteome analysis of breast cancer proteomes dataset as part of the DTU 22100 "R for Data Science" course.
schlogl2017's Repositories
schlogl2017/2015lab1
schlogl2017/awesome-microbes
List of computational resources for analyzing microbial sequencing data.
schlogl2017/berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
schlogl2017/biofx_python
Code for Mastering Python for Bioinformatics (O'Reilly, 2021, ISBN 9781098100889)
schlogl2017/courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
schlogl2017/cs231n.github.io
Public facing notes page
schlogl2017/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 175 universities.
schlogl2017/DGE_workshop
schlogl2017/DGE_workshop_salmon
schlogl2017/exercises
schlogl2017/getting_started_with_git
Learning Git
schlogl2017/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
schlogl2017/introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
schlogl2017/Learning-AWK-Programming
Learning AWK Programming, published by Packt
schlogl2017/learningsql-2875059
schlogl2017/neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
schlogl2017/ngs-course
Practice material for NGS and UNIX course.
schlogl2017/nnfs
Neural Networks from Scratch
schlogl2017/pathogen-informatics-training
schlogl2017/practicalgg
Practical ggplot2
schlogl2017/pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
schlogl2017/rnaseq
RNA-seq analyses.
schlogl2017/scRNA.seq.datasets
Collection of public scRNA-Seq datasets used by our group
schlogl2017/Sequence-Models-coursera
Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.
schlogl2017/single-cell-tutorial
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
schlogl2017/Stats-Maths-with-Python
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
schlogl2017/tfomics
schlogl2017/UDSMProt
Protein sequence classification with self-supervised pretraining
schlogl2017/workshop-advanced-python
Workshop on advanced python lead by Sergio Netotea
schlogl2017/workshop-neural-nets-and-deep-learning
NBIS workshop in Neural Nets and Deep Learning